{"title":"A Denoising Algorithm Combined with EMD and LMS for Precise Transmission Signal","authors":"Lei Song, Yongjun Cao, Yushan Zhou, Dongdong You","doi":"10.1155/2023/8853345","DOIUrl":null,"url":null,"abstract":"High accuracy and stability in mechanical transmission are crucial for various applications. In spite of the validity of mechanical enhancements, control algorithms’ fulfilment offers a cost-effective and efficient approach to mitigating the effects of noise signals. This study presents a hybrid algorithm that combines EMD with the least mean square (LMS) error to achieve online denoising. Within the algorithm, consecutive mean square error (CMSE) and the <svg height=\"8.8423pt\" style=\"vertical-align:-0.2064009pt\" version=\"1.1\" viewbox=\"-0.0498162 -8.6359 6.16729 8.8423\" width=\"6.16729pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"></path></g></svg>2-norm metric are employed to assess the similarity between intrinsic mode functions (IMFs) and the original signal; therefore, IMFs are separated into three distinct components: noise components, information components, and mixed components. The denoised signal is obtained by partial reconstruction. Subsequently, the denoised signal is employed as a reference signal in the LMS algorithm, which is utilized for practical processing. The performance evaluation of the developed algorithm employs simulation and experimental signals. The obtained results illustrate that the presented approach achieves sufficient accuracy and stability.","PeriodicalId":21915,"journal":{"name":"Shock and Vibration","volume":"74 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Shock and Vibration","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1155/2023/8853345","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ACOUSTICS","Score":null,"Total":0}
引用次数: 0
Abstract
High accuracy and stability in mechanical transmission are crucial for various applications. In spite of the validity of mechanical enhancements, control algorithms’ fulfilment offers a cost-effective and efficient approach to mitigating the effects of noise signals. This study presents a hybrid algorithm that combines EMD with the least mean square (LMS) error to achieve online denoising. Within the algorithm, consecutive mean square error (CMSE) and the 2-norm metric are employed to assess the similarity between intrinsic mode functions (IMFs) and the original signal; therefore, IMFs are separated into three distinct components: noise components, information components, and mixed components. The denoised signal is obtained by partial reconstruction. Subsequently, the denoised signal is employed as a reference signal in the LMS algorithm, which is utilized for practical processing. The performance evaluation of the developed algorithm employs simulation and experimental signals. The obtained results illustrate that the presented approach achieves sufficient accuracy and stability.
期刊介绍:
Shock and Vibration publishes papers on all aspects of shock and vibration, especially in relation to civil, mechanical and aerospace engineering applications, as well as transport, materials and geoscience. Papers may be theoretical or experimental, and either fundamental or highly applied.